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Record W2803904962 · doi:10.1103/physrevd.98.023008

Magnetosphere of a spinning black hole and the role of the current sheet

2018· article· en· W2803904962 on OpenAlexafffund
William E. East, Huan Yang

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsUniversity of GuelphPerimeter Institute
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceGovernment of CanadaPrinceton UniversityStanford University
KeywordsSpinningPhysicsBlack hole (networking)Context (archaeology)Spin-flipMagnetosphereCurrent sheetJet (fluid)PlasmaQuantum electrodynamicsClassical mechanicsMechanicsMagnetohydrodynamicsAstrophysicsQuantum mechanics

Abstract

fetched live from OpenAlex

We revisit the problem of a spinning black hole immersed in a uniformly magnetized plasma within the context of force-free electrodynamics. Such configurations have been found to relax to stationary jetlike solutions that are powered by the rotational energy of the black hole. We write down an analytic description for the jet solutions in the low black hole spin limit and demonstrate that it provides a good approximation to the configurations found dynamically. For characterizing the magnetospheres of rapidly spinning black holes, we find that the current sheet which forms in the black hole ergosphere plays an essential role. We study the properties of the current sheet and its importance in determining the jet solution and the rate at which energy is extracted from the black hole.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.359
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2018
Admission routes2
Has abstractyes

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